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Ford targeting highly autonomous vehicle for ride-sharing in 2021; new tech company investments, staffing up in Silicon Valley

Ford intends to have a high-volume, highly autonomous SAE level 4-capable vehicle in commercial operation in 2021 in a ride-hailing or ride-sharing service. To achieve this, the company is investing in or collaborating with four startups to enhance its autonomous vehicle development, doubling its Silicon Valley team and more than doubling its Palo Alto campus.

Autonomous vehicles in 2021 are part of Ford Smart Mobility, the company’s plan to be a leader in autonomous vehicles, as well as in connectivity, mobility, the customer experience, and data and analytics.

Building on more than a decade of autonomous vehicle research and development, Ford’s first fully autonomous vehicle will be an SAE-rated level 4-capable vehicle without a steering wheel or gas and brake pedals. It is being specifically designed for commercial mobility services, such as ride sharing and ride hailing, and will be available in high volumes.

Issued January 2014, SAE international’s J3016 provides a common taxonomy and definitions for automated driving. It defines more than a dozen key terms, including those italicized above, and provides full descriptions and examples for each level.

The report’s six levels of driving automation span from no automation to full automation. A key distinction is between level 2, where the human driver performs part of the dynamic driving task, and level 3, where the automated driving system performs the entire dynamic driving task.

These levels are descriptive rather than normative and technical rather than legal. They imply no particular order of market introduction. Elements indicate minimum rather than maximum system capabilities for each level. A particular vehicle may have multiple driving automation features such that it could operate at different levels depending upon the feature(s) that are engaged. Source: SAE International. Click to enlarge.

Ford has been developing and testing autonomous vehicles for more than 10 years. We have a strategic advantage because of our ability to combine the software and sensing technology with the sophisticated engineering necessary to manufacture high-quality vehicles. That is what it takes to make autonomous vehicles a reality for millions of people around the world.

—Raj Nair, Ford executive vice president, Global Product Development, and CTO

This year, Ford will triple its autonomous vehicle test fleet to be the largest test fleet of any automaker—bringing the number to about 30 self-driving Fusion Hybrid sedans on the roads in California, Arizona and Michigan, with plans to triple it again next year.

Ford was the first automaker to begin testing its vehicles at Mcity, University of Michigan’s simulated urban environment, the first automaker to publicly demonstrate autonomous vehicle operation in the snow and the first automaker to test its autonomous research vehicles at night, in complete darkness, as part of LiDAR sensor development.

The next decade will be defined by automation of the automobile, and we see autonomous vehicles as having as significant an impact on society as Ford’s moving assembly line did 100 years ago. We’re dedicated to putting on the road an autonomous vehicle that can improve safety and solve social and environmental challenges for millions of people – not just those who can afford luxury vehicles.

—Mark Fields, Ford president and CEO

To deliver an autonomous vehicle in 2021, Ford is announcing four key investments and collaborations that are expanding its strong research in advanced algorithms, 3D mapping, LiDAR, and radar and camera sensors:

  • Velodyne: Ford has invested in Velodyne (earlier post), the Silicon Valley-based leader in light detection and ranging (LiDAR) sensors. The aim is to quickly mass-produce a more affordable automotive LiDAR sensor. Ford has a longstanding relationship with Velodyne, and was among the first to use LiDAR for both high-resolution mapping and autonomous driving beginning more than 10 years ago.

  • SAIPS: Ford has acquired the Israel-based computer vision and machine learning company to further strengthen its expertise in artificial intelligence and enhance computer vision. SAIPS has developed algorithmic solutions in image and video processing, deep learning, signal processing and classification. This expertise will help Ford autonomous vehicles learn and adapt to the surroundings of their environment.

  • Nirenberg Neuroscience LLC: Ford has an exclusive licensing agreement with Nirenberg Neuroscience, a machine vision company founded by neuroscientist Dr. Sheila Nirenberg, who cracked the neural code the eye uses to transmit visual information to the brain. This has led to a powerful machine vision platform for performing navigation, object recognition, facial recognition and other functions, with many potential applications. For example, it is already being applied by Dr. Nirenberg to develop a device for restoring sight to patients with degenerative diseases of the retina. Ford’s partnership with Nirenberg Neuroscience will help bring humanlike intelligence to the machine learning modules of its autonomous vehicle virtual driver system.

  • Civil Maps: Ford has invested in Berkeley, California-based Civil Maps to further develop high-resolution 3D mapping capabilities. Civil Maps has pioneered an innovative 3D mapping technique that is scalable and more efficient than existing processes. This provides Ford another way to develop high-resolution 3D maps of autonomous vehicle environments Silicon Valley expansion.

Ford also is expanding its Silicon Valley operations, creating a dedicated campus in Palo Alto. Adding two new buildings and 150,000 square feet of work and lab space adjacent to the current Research and Innovation Center, the expanded campus grows the company’s local footprint and supports plans to double the size of the Palo Alto team by the end of 2017.

Since the new Ford Research and Innovation Center Palo Alto opened in January 2015, the facility has rapidly grown to be one of the largest automotive manufacturer research centers in the region. Today, it is home to more than 130 researchers, engineers and scientists, who are increasing Ford’s collaboration with the Silicon Valley ecosystem.

Research and Innovation Center Palo Alto’s multi-disciplinary research and innovation facility is the newest of nearly a dozen of Ford’s global research, innovation, IT and engineering centers. The expanded Palo Alto campus opens in mid-2017.


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This is the clearest statement about intent to make fully autonomous vehicles that I have seen from any of the old auto-makers. And the best part of it is that Ford believes they can have a volume product ready by 2021. GM’s CEO has said they need 10 years or until 2025 for full-autonomy cars so Ford is clearly more ambitions than GM on this all important issue. I also like that Ford realizes that fully self driving vehicles are by far the most important thing that will happen in the auto-industry since the invention of the mass produced Ford T with a combustion engine.

What Ford is not so clear about is the plan for how to get from where they are now with 10 test vehicles to a mass produced fully autonomous car that is approved for autonomous taxi driving. Tesla’s plan for this is clearer IMO. Tesla will keep improving its autopilot offered for all of its cars until it can drive 10 times safer in all circumstances than the average human driver. Then they will use their massive fleet data on accidents with autopilot engaged to get approval to operate their vehicles without driver oversight, i.e. as fully autonomous vehicles. In terms of statistics you need about 6 billion miles per unique driving environment (like USA) to scientifically prove that your system drives 10 times safer than the average human driver. 6 billion miles can be driven by 400,000 cars that drive 15,000 miles per year each. Ford, Tesla, Google, GM, Uber and everyone else also need that statistical documentation before they can get the permission to operate their cars without human drivers in control of the car. Tesla has realized this but I am not sure the old auto-industry or even Google get it yet. Driven around with 100 test vehicles will not be enough by any means. We need 400,000 vehicles to make a proper statistics.

Also Ford will stick with LIDAR. This is not the right call because Lidar cannot see color as needed to see a traffic light and Lidar cannot see in heavy rain or fog as radar can. Ford’s vehicles will therefore also need cameras and radar. Tesla’s next autopilot hardware will get more cameras and radar but no Lidar as it is not needed for anything as cameras and radar can do all that Lidar can do and them some more like color and heavy fog driving. My point is that Lidar is not needed for making fully autonomous cars but cameras are and radar are needed for giving autonomous cars abilities that human drives do not have because we cannot see in heavy rain or fog.


Lidar will be needed, as well as radar and an array of colour (and perhaps mono or IR) cameras. And probably cm accuracy GPS (say 2-5cms).
Cameras are cheap, high res and colour, but they can get confused by repeating patterns in scenes which Lidar would be able to see. Radar doesn't have the spatial resolution but can see through fog, rain etc and so has a place.
IMO, they will throw lots of different sensors at the problem initially and over the years may reduce them, or may just reduce the costs and leave them in place.
The problem is not buying the sensors, it is fusing the data from many disparate sensors together.
Just because humans can drive using colour stereo vision does not mean that this is the best way to get a machine to do it.

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